Triple

T1108806
Position Surface form Disambiguated ID Type / Status
Subject Tin Lizzie E25545 entity
Predicate alsoKnownAs P39 FINISHED
Object Flivver E26005 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Flivver | Statement: [Tin Lizzie, alsoKnownAs, Flivver]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flivver
Context triple: [Tin Lizzie, alsoKnownAs, Flivver]
  • A. Flivver chosen
    Flivver is a colloquial nickname for the Ford Model T, the iconic early 20th-century mass-produced automobile that revolutionized personal transportation.
  • B. Whizzer
    Whizzer was the well-known nickname of Byron Raymond White, a prominent American football player who later became an Associate Justice of the U.S. Supreme Court.
  • C. Flying J
    Flying J is a chain of highway travel centers and truck stops in North America, known for providing fuel, food, and amenities for professional drivers and motorists.
  • D. Vespa
    Vespa is a genus of large social wasps best known for including the true hornets found across Europe and Asia.
  • E. Velo
    Velo is a nicotine pouch brand owned by British American Tobacco, marketed as a smokeless alternative to traditional cigarettes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a49428d4448190b3b36991ceae87ce completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b9e6134481909f348986a25f65c6 completed March 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c4f65888190b48c2d220e62a26b completed March 7, 2026, 4:03 p.m.
Created at: March 1, 2026, 7:43 p.m.